Bushfire Prevention — Data-Driven Powerline Installation and Brush Monitoring

About one month ago, Southern Australia experienced an extreme heat wave that melted pavement, boiled bats, and exacerbated the fire potential of an already dried out landscape. Rather than being an anomaly, this degree of heat wave may be closer to what, in the future, we view as the norm.

A report released in 2016 by the Bureau of Meteorology paints a pretty bleak picture:

  • May-July rainfall has reduced by around 19% since 1970 in the Southwest of Australia;
  • Australia’s climate has warmed in both mean surface air temperature and surround sea surface temperature by around 1°C;
  • the duration and frequency of extreme heat events has increased across large parts of Australia;
  • there has been an increase in extreme fire weather, and a longer fire season, across large parts of Australia since the 1970s.

While extreme heat may not directly cause fire, less rainfall and hotter temperatures, intensify the likelihood of sever fire weather.

This logic is not lost on the power distribution companies that manage the Southern Australian transmission lines. German reinsurance company Munich RE explains, “during days of extreme fire danger, the percentage of fires caused by electrical distribution assets rises dramatically above the long-term average.”

This equates to a loss potential of thousands of homes, hundreds of lives and millions of dollars. In 2009, the Kilman Fire destroyed 1,242 homes and killed 119 people. A power distribution company was partly blamed and eventually agreed to pay A$378M to over 5,000 plaintiffs. The State of Victoria also had to pay out a whopping A$103.6MM.

What are the power companies and Australian States to do?

Prevention, specifically burying powerlines underground and monitoring brush loads.

Burying powerlines underground can account for significant cost reduction; according to Munich RE, “expressed in monetary terms, the ratio of benefits of underground electricity wires relative to costs projected up until 2050 was estimated as high as 3:1.”

Brush load monitoring helps determine fire risk levels. This factors into a number of other decisions, notably, prioritized brush clearing and the variable risk an insurer is willing to take on.

To understanding areas subject to highest potential risk for a transmission failure and brush load concentrations, we have made available, through the Planet OS Datahub API, a compilation of datasets sourced from the Australian Bureau of Meteorology. The datasets are a combination of precipitation, temperature and NDVI data compiled over the past 100 years.

If your company is exposed to environmental risk, the Planet OS Datahub provides access to 63 high-quality datasets from the world’s leading scientific organizations and weather data publishers. To learn more about our data services, and our simple, easy-to-use API, visit data.planetos.com.